Skip to main content

Open Source Data Quality Monitoring

Project description

Logo

Open Source Data Quality Monitoring.

License Versions coverage coverage Status

⭐️ If you like it, star the repo

| Documentations | Slack Community |

Why Data Monitoring?

APM (Application Performance Monitoring) tools are used to monitor the performance of applications. APM tools are mandatory part of dev stack. Without AMP tools, it is very difficult to monitor the performance of applications.

why_data_observability

But for Data products regular APM tools are not enough. We need a new kind of tools that can monitor the performance of Data applications. Data monitoring tools are used to monitor the data quality of databases and data pipelines. It identifies potential issues, including in the databases and data pipelines. It helps to identify the root cause of the data quality issues and helps to improve the data quality.

What is datachecks?

Datachecks is an open-source data monitoring tool that helps to monitor the data quality of databases and data pipelines. It identifies potential issues, including in the databases and data pipelines. It helps to identify the root cause of the data quality issues and helps to improve the data quality.

Datachecks can generate several reliability, uniqueness, completeness metrics from several data sources

Reports: Data Quality Visualisation

You can generate with just one command. It generates a beautiful data quality report with all the metrics. This html report can be shared with the team.

why_data_observability

CLI: Data Quality Visualisation in Bash

Data quality report can be generated in the terminal. It is very useful for debugging. All it takes is one command.

why_data_observability

Getting Started

Install datachecks with the command that is specific to the database.

Install Datachecks

To install all datachecks dependencies, use the below command.

pip install dcs-core -U

Create the config file

With a simple config file, you can generate data quality reports for your data sources. Below is the sample config example. For more details, please visit the config guide

Run from CLI

Generate Report in Terminal

dcs-core inspect -C config.yaml

Generate HTML Report

dcs-core inspect -C config.yaml  --html-report

Please visit the Quick Start Guide

Supported Data Sources

Datachecks supports sql and search data sources. Below are the list of supported data sources.

Data Source Type Supported
Postgres Transactional Database :thumbsup:
MySql Transactional Database :thumbsup:
MS SQL Server Transactional Database :thumbsup:
Oracle Transactional Database :thumbsup:
DB2 Transactional Database :thumbsup:
SAP Sybase Transactional Database :thumbsup:
OpenSearch Search Engine :thumbsup:
Elasticsearch Search Engine :thumbsup:
GCP BigQuery Data Warehouse :thumbsup:
DataBricks Data Warehouse :thumbsup:
Snowflake Data Warehouse :thumbsup:
AWS RedShift Data Warehouse :thumbsup:

Metric Types

Validation Funtions Description
Reliability Reliability functions detect whether tables/indices/collections are updating with timely data
Numeric Distribution Numeric Distribution functions detect changes in the numeric distributions i.e. of values, variance, skew and more
Uniqueness Uniqueness functions detect when data constraints are breached like duplicates, number of distinct values etc
Completeness Completeness functions detect when there are missing values in datasets i.e. Null, empty value
Validity Validity functions detect whether data is formatted correctly and represents a valid value

Overview

datacheck_architecture

What Datacheck does not do?

Community & Support

For additional information and help, you can use one of these channels:

  • Slack (Live chat with the team, support, discussions, etc.)
  • GitHub issues (Bug reports, feature requests)

Contributions

:raised_hands: We greatly appreciate contributions - be it a bug fix, new feature, or documentation!

Check out the contributions guide and open issues.

Datachecks contributors: :blue_heart:

Telemetry

Usage Analytics & Data Privacy

License

This project is licensed under the terms of the APACHE 2 License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dcs_core-0.8.1.tar.gz (1.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

dcs_core-0.8.1-py3-none-any.whl (1.2 MB view details)

Uploaded Python 3

File details

Details for the file dcs_core-0.8.1.tar.gz.

File metadata

  • Download URL: dcs_core-0.8.1.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.11 Darwin/24.1.0

File hashes

Hashes for dcs_core-0.8.1.tar.gz
Algorithm Hash digest
SHA256 89d51e5900518954d951acb11cda50cc72290ed0552c3a8c135ba0dcf9ca62ed
MD5 a6f7656574652afc657cb7192e7f6438
BLAKE2b-256 e8c3edcdb99a667b698156db3f5762f8b6dc6da510a777cd63946d212bd4ebf9

See more details on using hashes here.

File details

Details for the file dcs_core-0.8.1-py3-none-any.whl.

File metadata

  • Download URL: dcs_core-0.8.1-py3-none-any.whl
  • Upload date:
  • Size: 1.2 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.8.3 CPython/3.9.11 Darwin/24.1.0

File hashes

Hashes for dcs_core-0.8.1-py3-none-any.whl
Algorithm Hash digest
SHA256 16b13efe405dcfc90e7055fd56e7e0c0585e8b05445c108a95070ce008ef85af
MD5 f1ad895e203b9b1208b5f3719f21151a
BLAKE2b-256 fab9cd2905f78c7df1cfeb2c1cf64a5ecee1ac9d15331bd8f14245db544322f3

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page